No Little Plans: Alternative Building and Transportation Visions for Toronto. CITY OF TORONTO ARCHIVES
Bibliographic record
Abstract
The title for the No Little Plans exhibition comes from an apocryphal quote by the city planner and architect Daniel Burnham (1846-1912), who called on his comrades in the building trade to "make no little plans.... Make big plans; aim high in hope and work, remembering that a noble, logical diagram once recorded will never die, but long after we are gone will be a living thing." 1 The quotation, reprinted in the city of Toronto Archives' exhibition brochure, evokes a particularly archival sentiment: the dream of preserving the past as a living experience.hence, the exhibition, in presenting records of an imagined future Toronto, as glimpsed through the plans and schemes of the past, affords the spectator a tremendously rich view of municipal history that moves beyond the typical checklist of historical progress, the mere notation of accomplishments from one outcome to the next, into the realm of unrealized dreams and ambitions.in this space, we are not surprised to rediscover that the problems of the urban experience in 2015 -affordable housing, urban density, public transportation, infrastructure, funding, and taxes -are also the problems of 1915, 1955, and the entire epoch of modern memory.The exhibition presents a small selection of the projects explored in the two volumes of Unbuilt Toronto by Mark Osbaldeston, published by Dundurn Press in 2008 and 2011 respectively.The displays include units on housing,
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.052 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".